BOOS national activities in 2016 part2 Observeration and services BOOS STG

Transcription

1 BOOS national activities in 2016 part2 Observeration and services BOOS STG

2 CMEMS Ocean State Report: Baltic Sea inflow Eutrophication, hypoxia, low sea level event

3 Eutrophication: summer bloom coverage Figure 2. Time series of summer bloom spatiotemporal coverage (day km2) ( )

4 Eutrophication: bottom oxygen Oxygen situation near the seabed in the Baltic Sea in 15 August 2014, 2015 and 2016, BAL MFC Oxygen situation near the seabed in the Baltic Sea in August 2014, 2015 and 2016 SYKE

5 BOOS + INSTAC Integrate Fixed platforms ftp.boos.org Integrate Tide gauges Integrate Moored buoys Integrate Ferryboxes Vessels Distribution of In-situ products BOOS Users

6 Platforms SMHI acquires data from ~300 fixed oceanographic stations ~10 ferryboxes + 5 icebreakers ~800 CT stations in the Baltic Sea Fixed platforms (FP) Tide gauges (TG) Moored buoys (MB) Ferrybox-lines (FB) Ice-breakers (FB) Monitoring stations (CT)

7 Coloured dissolved organic matter, CDOM fdom measurements in several ferries since 2011, in Utö since 2015 Huge increase of CDOM from Bothnian Sea to Bothnian Bay. Late summer increase. Closer evaluation needed to fine-tune Baltic C-budget

8 Nurtient monitoring Water samples in 2015 on M/S Finnmaid Marine Research Centre

9 SHIP - Implementation project at SMA-SMHI Targets in the SHIP project directive: - One common and harmonised Swedish tide gauge network - Sea level data of better accuracy, continuous time series - Open and faster access to quality controlled real-time and archive data - Leads to that the objectives of the FAMOS Odin is achieved: safer and more cost effective shipping routes

10 Present Swedish tide gauge networks Class I Upgrade with logger 26 stations (23 SMHI + 3 SMA) Class II Upgrade without logger 27 stations (27 SMA) Class III Unchanged, temporary 5 stations (3 SMHI + 2 SMA) Class IV Will be phased out 5 stations (1 SMHI + 4 SMA)

11 Future Swedish tide gauge network Real-time data in RH2000 from 53 stations 1-min values with 1 cm accuracy Real-time QC + Archive MQC Class I Upgrade with logger 26 stations (23 SMHI + 3 SMA) Class II Upgrade without logger 27 stations (27 SMA) Class III Unchanged, temporary 5 stations (3 SMHI + 2 SMA)

12 Present work Specification for a procurement of two different sensor are finalized All stations will be connected to RH2000 (BSCD2000) in 2017 Joint service organisation SMA-SMHI: levelling, maintenance, service personel etc. Inventory of stations and test of equipment will continue Implementation of RTQC-routines to all data

13 Institute of Oceanology PAS Typical r/v Oceania schedule

14 IOPAN Physical oceanography 4 cruises per /year - route along the NS water inflow Localizations of the main high resolution CTD/O 2 transect Previously cruises (available data)

15 IOPAN: Argo floats Trajectory of the first Argo float at the Southern Baltic. WMO , 29 November February 2017 Trajectory of the second Argo float at the Southern Baltic. WMO , 18 March May 2017

16 Argo floats TS diagram, salinity and temperature profiles WMO WMO ,

17 Block diagram of the SatBaltic Operating System Satellite VIS, IR1, IR2, Microwave BASIC INPUT DATA: Global meteorological model data Routine meteo- and hydrological data SATBALTIC OPERATING SYSTEM D0 DESAMBEM DIAGNOSTIC SYSTEM INITIAL PROCESSING B0 BALTFOS PROGNOSTIC SYSTEM INITIAL PROCESSING D1 ATMOSPHERIC PARAMETERS clouds, AOT, ozone, water vapour p, U 10,... B1 WEATHER MODEL pressure (p), wind speed (U 10 ), humidity, air temperature,... CURRENT structural and functional properties of the sea D2 D3 D4 PHYSICAL PROPERTIES OF THE SEA SURFACE temperature SST, ice cover ICE, solar irradiance E, radiation balance NET BIOOPTICAL PROPERTIES OF THE SEA Surface chlorophyll a C a (0), Irradiance attenuation K d (λ), chlorophyll depth profile C a (z), nutrients N, P, primary production PP OTHER IDENTIFIED PARAMETERS thermal fronts, upwellings, phytoplankton blooms, oil spills SST SST E, ICE, C a (0) C a (0) different paremeters B2 B3 MODELS: HYDRODYNAMIC, THERMODAYNAMIC SEA ICE temperature SST, T, salinity S,currents v, sea level, ice properties ECOHYDRODYNAMIC MODELS chlorophyll a, nutrients, biomass of different taxonomic groups of phytoplankton B4 OTHER PREDICTED PARAMETERS thermal fronts, upwellings, phytoplankton blooms, oil spills PREDICTED structural and functional properties of the sea Data transfer for an overcast sky (lack of satellite data for the DESAMBEM algorithm) Data transfer for a cloudless sky (data assimilation to improved the ECOSAT algorithm) Data transfer always required to make the most of the DESAMBEM and ECOSAT algorithms blue letters in the description denote parameters computed directly from data supplied by one satellite CALIBRATION / VALIDATION DATA (buoys, ships, shore stations) red letters in the description denote parameters computed from data supplied directly or indirectly by several satellite sources, and / or by the SatBaltic System

18 First testing deployment of the Stolpe Channel Buoy Example of results from February

19 IOPAN bio-optical activity on the Baltic about 4-5 bio-optical cruises each year stations on the each cruise one of the goals - calibration and validation of satellite data

20 Bio-optical cruise May 2016

21 SatBałtyk buoy Measuring buoy SatBałtyk (Gulf of Gdańsk) 'E, ' N Atmospheric parameters Downward shortwave irradiance (range nm) Air temperature Wind speed and direction Atmospheric pressure Relative humidity Underwater parameters on 0, 1 and 5 m Water temperature Salinity Dissolved oxygen chlorophyll a CDOM fluorescence Light absorption and attenuation Downward and upward irradiance

22 ggp [mgc m -2 day -1 ] Monthly averages of daily primary production in In Gdansk Bay 1. PP in March increased from 2010 to 2015 by 30% 2. PP annual max in summer has two lows in in 2012 and

23 IOPAN other activities on the Baltic Acoustics: -. - underwater noise Marine Chemistry and Biochemistry -. CHEMSEA -Chemical Munitions Search & Assessment MODUM - Towards the Monitoring of Dumped Munitions Threat DAIMON Decision Aid for Marine Munitions : how to proceed with the identified and mapped warfare objects

24 Finnish Meteorological Institute FMIs Argo history ARGO_FIN 2010 July, Atlantic Ocean since then 2011 first short tests in the Baltic Sea 2012 May December first long deployment in Bothnian Sea August, first long deployment in Gotland Deep Now, 21 Argo missions, 5 active in May missions in the Atlantic/North Sea, 3 active in May missions in the Baltic, 2 active in May 2017 Baltic Sea floats reused Data from the 21 floats is available in Coriolis Argo data center Finland is a partner in Euro-Argo (FMI is representing unit)

25 Challenges in Baltic Sea Brackish water and large variations in density Floats need to be balanced for a certain area Heavy marine traffic risk of collision Seasonal ice cover ice avoidance algorithms Shallow depths constant monitoring needed, buoyancy accuracy ±10-30 m NOTE! It has turned out that standard floats work in the Baltic Sea. photograph by Petra Roiha, FMI 25

26 First experiments in the Bothnian Sea in 2012 Half a year mission May 17 -> Dec 5, 2012 Over 200 profiles acquired Managed to stay all the time away from shores Required constant modifying of the diving instructions to avoid bottom contact

27 Argo's in Gotland basin Fine-tuned programming Deep profile testing bio sensors testing deployed at Aug 14, 2014 Managed to stay all the time away from shores

28 Current activities Testing Argo floats in ice conditions Continue applying data for model validation and development Experimenting with data assimilation Application to process studies Some manuscripts under construction 28 photograph by Petra Roiha, FMI

29 Argo data available in Coriolis Coriolis Argo-page: All floats in a list: One float by number (e.g ): As netcdf via ftp: ftp://ftp.ifremer.fr/ifremer/argo/dac/coriolis/ Also via MyOcean data selection: NOTE! In Coriolis data is available both as ASCII (csv) and netcdf (nc)

30 Navigation buoys

31 Integration of marine metoc data into AIS system + additional wave data GPRS IP AtoN Server FrontEnd software PaSS AIS Router sofware Signal analyse Internet connection to AIS network GPRS SMS Wave Height WHAPAS HMS-HMD Hydro-Meteo AIS Server/ VHF System AIS messages M 21, M12, M14 M8

32 Use of buoy motion data for wave estimate 3D motion data acquisition: 5 samples in 1 second (3x2B binary) 150 second registration time 15 minute/ 4 times in hour interval Continuous registration Motion data transmission: TCP/IP over GPRS, AtoN monitoring 15 min interval (3kB binary, 12kB/hour) Continuous 72kB/hour Motion data analysis: Timely filtering Mathematical analysis Calibration with reference data Wave data output: Record to data base Save special text file Broadcast via AIS Router

33 Validation of wave data obtained from the buoys Latitude [N] Kuradimuna NM NM Karbimadal NM185 NM186 NM170 Pressure sensor based wave gauge 2 measurement periods 3 weeks each September and November Longitude [E]

34 Web-based user interface: on-line.msi.ttu.ee/metoc 22 wavebuoys in Estonian waters + 12 stationary pressure gauges

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36 Outline of PAH concentration measurements Analysed 55 ship voyages ( ), 960 datapoints each, in all e.g. very good ensemble for statistical analysis Max PAH concentration 0,36 µg/l Remarkable variability of PAH concentrations near the coasts and open sea General pattern of PAH concentration spatial distribution seems to be stable No sudden concentration rises which directly would indicate the oil spills, have been detected during the observation periood, all PAH comcentrations stay far below those defining the oil spill Some anomalies of PAH concentrations were noticed and could be investigated further although amplitude of such anomalies were in same order with UviLux sensor signal/noise level

37 Summary Asset for in-situ oil detection and monitoring is developed based on FerryBox technology and equipped with on-line data management Test of the system on board M/S BALTIC QUEEN performed and 2 month of data single measurement points statistically analyzed, further analysis foreseen Measured PAH concentrations are not absolute values, but rather than relative, but still variability patterns could be estimated Fouling problem should lessen, when new cleaning system (more frequent) will be operational Validation of UviLux sensor against lab analysis is foreseen in May 2017, report in August 2017

38 Estonian Marine areas Information System EMIS Operational model HCM-EST, Still under construction but better than nothing BOOS Annual meeting May 22, 2017, DMI, Copenhagen 38